In today's global economy, obtaining a high-quality translation of content (e.g. text, graphic design, document layout, etc.) from an original source language to a target language becomes more and more important. While there are many machine, computer based, translation systems, such as Google® Translate, professional human translators are still needed to produce an accurate, high-quality translation. Unfortunately, human translators often err and produce an inadequate translation. The common solution today is to have a proofreader, editor, or translation reviewer read the translated content and correct it as needed. This solution is expensive, slow and inadequate.
Language translation of textual content is also a complicated process due to a variety of factors, such as syntax, semantics, and language ambiguity that occurs in various aspects in natural language processing, e.g. lexical ambiguity, case ambiguity and referential ambiguity. Therefore, to ensure a high-quality translation, a translator must translate into a language that they are fluent in both written and oral form, and they must also have a sufficient technical knowledge of the field being translated in order to have a full understanding of the subject matter. It is no wonder, then, that translations by professional translators are often of variable quality, and why machine translations are normally riddled with errors.
A bad translation can cause significant damage; sometimes even a single word can drastically change the meaning of the entire paragraph. Machine translation solutions are often not accurate enough and the existing methods for evaluating translation quality are cumbersome, slow and expensive. Usually a supervising proofreader (i.e. a translation reviewer) checks the translation and corrects it if errors are found. A single proofreader may not locate all the errors in the translation especially if he or she is under time pressure.
The level of quality of a given translation is hard to determine as it is a very subjective matter. In essence, a translation is considered to be of “good quality” if enough people with control of both the source (i.e. original) content and the target (i.e. translated) content consider it to be an accurate and succinct translation. But, with the existing methods, submitting a project for proofreading or review by more than one proofreader will result is unacceptable costs in terms of time and money.
Therefore, there is a need within the art of human and machine language translations for an efficient, economical, reliable, and timely method for a computer system to automatedly evaluate the quality and accuracy of a human or machine language translation.